samsung SM-G715FN
Geekbench AI Score
31
Single Precision Score
529
Half Precision Score
407
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | benched |
| Upload Date | November 03 2025 08:10 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | samsung SM-G715FN |
| Model ID | samsung SM-G715FN |
| Motherboard | exynos9611 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3337 revision 2 |
| Base Frequency | 1.74 GHz |
| Cluster 1 | 4 Cores @ 1.74 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 3.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
34.8 IPS |
|
|
Image Classification (HP)
|
100% |
323
60.0 IPS |
|
|
Image Classification (Q)
|
97% |
309
57.7 IPS |
|
|
Image Segmentation (SP)
|
73% |
248
4.28 IPS |
|
|
Image Segmentation (HP)
|
100% |
483
7.84 IPS |
|
|
Image Segmentation (Q)
|
98% |
434
7.06 IPS |
|
|
Pose Estimation (SP)
|
100% |
1067
1.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
2126
2.48 IPS |
|
|
Pose Estimation (Q)
|
95% |
2084
2.44 IPS |
|
|
Object Detection (SP)
|
1% |
0
13.6 IPS |
|
|
Object Detection (HP)
|
99% |
329
26.1 IPS |
|
|
Object Detection (Q)
|
83% |
301
24.3 IPS |
|
|
Face Detection (SP)
|
0% |
0
7.47 IPS |
|
|
Face Detection (HP)
|
100% |
1118
13.3 IPS |
|
|
Face Detection (Q)
|
96% |
941
11.2 IPS |
|
|
Depth Estimation (SP)
|
1% |
2
5.21 IPS |
|
|
Depth Estimation (HP)
|
98% |
1242
9.60 IPS |
|
|
Depth Estimation (Q)
|
62% |
975
9.26 IPS |
|
|
Style Transfer (SP)
|
100% |
1375
1.77 IPS |
|
|
Style Transfer (HP)
|
100% |
2876
3.70 IPS |
|
|
Style Transfer (Q)
|
98% |
2851
3.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
454
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
815
30.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
797
29.5 IPS |
|
|
Text Classification (SP)
|
35% |
13
123.7 IPS |
|
|
Text Classification (HP)
|
35% |
17
152.8 IPS |
|
|
Text Classification (Q)
|
32% |
11
148.2 IPS |
|
|
Machine Translation (SP)
|
100% |
211
3.64 IPS |
|
|
Machine Translation (HP)
|
100% |
285
4.91 IPS |
|
|
Machine Translation (Q)
|
43% |
65
3.80 IPS |
